Individual tags are attached to players and are programmed for a specific reporting rate, such as 25 Hz (i.e. 40 ms/pt). Location information is received from the tag every 40 ms and used within a location tracking system to calculate a raw location point for the tracked object each 40 ms. Where multiple tags are used, these raw location points are calculated for each tag. The location tracking system then filters the raw location points to generate location data for the tracked object at a uniform rate (typically 100 ms).
Raw location points are filtered using a fixed-time moving average filter that has a moving average filter period of 500 ms. Thus, every 100 ms, which is the output period, the location tracking system calculates a “time corrected” moving average of raw location points for the last 500 ms. Where everything is working correctly and raw locations points are calculated at 25 Hz (i.e., each 40 ms), the filter calculates the moving average for 12 or 13 raw location points (500 ms filter period/40 ms per raw location point) to generate the location data.
However, these raw location points may be missed for a variety of reasons (e.g., physical blocking of wireless transmissions from the tag, variations in tag orientation, etc). The moving average that is calculated by the filter is “time corrected,” where each raw location point is weighted according to its arrival time. Thus, when one (or more) raw location point is missed, the calculated moving average value is effectively calculated for a different delay period. This affects the delay of the filter.
In the above example using the 500 ms moving average filter, there is a 250 ms filter delay (i.e., half the filter width) for the output location data. That is, each calculated moving average value defines the location of the tag 250 ms in the past. Provided that this delay is constant, it is handled within the location tracking system. However, the “time corrected” aspect of the moving average calculation maintains this fixed filter delay even in the face of some missing 40 ms raw data points, thereby introducing error into the location data.
The standard filter described above operates satisfactorily in normal operation but has shortcomings in certain sport-specific cases. In football for example, each player has at least one tag for tracking location. When the players line up before the start of each play, a series of specific conditions may arise.
For one, the players are substantially stationary, and when providing a “zoomed in” graphic representation of the location data of these players, any minor perturbation (noise) in the location data becomes more visible and more apparent than when the player is moving.
Alternatively, some of the players are closely crowded together, which causes more blocking of radio transmissions from the tags, and thereby more missing raw location points as well as slightly less accuracy for raw location points that are received by the location tracking system.
Additionally, many players may be leaning over, which changes the orientation of the tags, which are typically attached to the shoulders of the players. This change in orientation typically results in more raw location points being missed by the location tracking system as well as slightly less accuracy for raw location points that are received by the location tracking system.